The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it may be described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present technology.
In materials informatics, a key step that bridges the raw data and machine learning is the data representation, which transforms the raw data into fingerprints/features that computer can analyze. While several methods have been proposed to represent crystal structures of inorganic materials, they fail to compare the similarity between two distinct structures.
In previous studies, structure matching algorithms were employed to match the structure of two compounds through a continuous transformation, yielding a degree of distortion required to match two structures. This method does not provide quantitative information on structural similarity.
Accordingly, it would be desirable to provide an improved method for the quantitative analysis of inorganic crystal structures.